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An adaptive scheduling protocol for multi-scale sensor network architecture 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Santashil PalChaudhuri David B. Johnson Aruba Networks Sunnyvale CA Department of Computer Science Rice University Houston TX

ISBN: (纸本)9783540730897

In self-organizing networks of battery-powered wireless sensors that can sense, process, and communicate, energy is the most crucial and scarce resource. However, since sensor network applications generally exhibit specific limited behaviors, there is both a need and an opportunity for adapting the network architecture to match the application in order to optimize resource utilization. Many applications-such as large-scale collaborative sensing, distributed signal processing, and distributed data assimilation-require sensor data to be available at multiple resolutions, or allow fidelity to be traded-off for energy efficiency. We believe that cross-layering and application-specific adaptability are the primary design principles needed to build sensor networking protocols. In previous work, we proposed an adaptive cross-layered self-organizing hierarchical data service under COMPASS architecture, that enables multi-scale collaboration and communication. In this paper we propose a time division multiplexing medium scheduling protocol tailored for this hierarchical data service, to take advantage of the communication and routing characteristics to achieve close to optimal latency and energy usage. We present an analytical proof on the bounds achieved by the protocol and analyze the performance via detailed simulations.

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Energy efficient intrusion detection in camera sensor networks 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Primoz Skraba Leonidas Guibas Department of Electrical Engineering Stanford University Stanford CA Department of Computer Science Stanford University Stanford CA

ISBN: (纸本)9783540730897

The problem we address in this paper is how to detect an intruder moving through a polygonal space that is equipped with a camera sensor network. We propose a probabilistic sensor tasking algorithm in which cameras sense the environment independently of one another, thus reducing the communication overhead. Since constant monitoring is prohibitively expensive with complex sensors such as cameras, the amount of sensing done is also minimized. To be effective, a minimum detection probability must be guaranteed by the system over all possible paths through the space. The straightforward approach of enumerating all such paths is intractable, since there is generally an infinite number of potential paths. Using a geometric decomposition of the space, we lowerbound the detection probability over all paths using a small number of linear constraints. The camera tasking is computed for set of example layouts and shows large performance gains with our probabilistic scheme over both constant monitoring as well as over a deterministic heuristic.

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distributed coalition formation in visual sensor networks: a virtual vision approach 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Faisal Qureshi Demetri Terzopoulos Dept. of Computer Science University of Toronto Toronto ON Canada Dept. of Computer Science University of Toronto Toronto ON Canada and Computer Science Dept. University of California Los Angeles CA

ISBN: (纸本)9783540730897

We propose a distributed coalition formation strategy for collaborative sensing tasks in camera sensor networks. The proposed model supports taskdependent node selection and aggregation through an announcement/bidding/ selection strategy. It resolves node assignment conflicts by solving an equivalent constraint satisfaction problem. Our technique is scalable, as it lacks any central controller, and it is robust to node failures and imperfect communication. Another unique aspect of our work is that we advocate visually and behaviorally realistic virtual environments as a simulation tool in support of research on largescale camera sensor networks. Specifically, our visual sensor network comprises uncalibrated static and active simulated video surveillance cameras deployed in a virtual train station populated by autonomously self-animating pedestrians. The readily reconfigurable virtual cameras generate synthetic video feeds that emulate those generated by real surveillance cameras monitoring public spaces. Our simulation approach, which runs on high-end commodity PCs, has proven to be beneficial because this type of research would be difficult to carry out in the real world in view of the impediments to deploying and experimenting with an appropriately complex camera network in extensive public spaces.

关键词： sensor coordination and control video surveillance camera sensor networks distributed coalition formation

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Efficient computation of minimum exposure paths in a sensor network field 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Hristo N. Djidjev Los Alamos National Laboratory Los Alamos NM

ISBN: (纸本)9783540730897

The exposure of a path p is a measure of the likelihood that an object traveling along p is detected by a network of sensors and it is formally defined as an integral over all points x of p of the sensibility (the strength of the signal coming from x) times the element of path length. The minimum exposure path (MEP) problem is, given a pair of points x and y inside a sensor field, find a path between x and y of a minimum exposure. In this paper we introduce the first rigorous treatment of the problem, designing an approximation algorithm for the MEP problem with guaranteed performance characteristics. Given a convex polygon P of size n with O(n) sensors inside it and any real number Ɛ > 0, our algorithm finds a path in P whose exposure is within an 1 + Ɛ factor of the exposure of the MEP, in time O(n/Ɛ2ψ), where ψ is a topological characteristic of the field. We also describe a framework for a faster implementation of our algorithm, which reduces the time by a factor of approximately Θ(1/Ɛ), by keeping the same approximation ratio.

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Dwarf: delay-aware robust forwarding for energy-constrained wireless sensor networks 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Mario Strasser Andreas Meier Koen Langendoen Philipp Blum ETH Zurich Switzerland Delft University of Technology The Netherlands Siemens Building Technologies Switzerland

ISBN: (纸本)9783540730897

With the field of wireless sensor networks rapidly maturing, the focus shifts from "easy" deployments, like remote monitoring, to more difficult domains where applications impose strict, real-time constraints on performance. One such class of applications is safety critical systems, like fire and burglar alarms, where events detected by sensor nodes have to be reported reliably and timely to a sink node. A complicating factor is that systems must operate for years without manual intervention, which puts very strong demands on the energy efficiency of protocols running on current sensor-node *** we are not aware of a solution that meets all requirements of safety-critical systems, i.e. provides reliable data delivery and low latency and low energy consumption, we present Dwarf, an energy-efficient, robust and dependable forwarding algorithm. The core idea is to use unicast-based partial flooding along with a delay-aware node selection strategy. Our analysis and extensive simulations of real-world scenarios show that Dwarf tolerates large fractions of link and node failures, yet is energy efficient enough to allow for an operational lifetime of several years.

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SNTS: sensor network troubleshooting suite 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Mohammad Maifi Hasan Khan Liqian Luo Chengdu Huang Tarek Abdelzaher University of Illinois at Urbana Chamapign Department of Computer Science

ISBN: (纸本)9783540730897

sensor network troubleshooting is a notoriously difficult task, further exacerbated by resource constraints, unreliable components, unpredictable natural phenomena, and experimental programming paradigms. This paper presents SNTS (sensor Network Troubleshooting Suite), a tool that performs automated failure diagnosis in sensor networks. SNTS can be used to monitor network conditions using simple visualization techniques as well as to troubleshoot deployed distributed sensor systems using data mining approaches. It is composed of (i) a data collection front-end that records events internal to the network and (ii) a data processing back-end for subsequent analysis. We use data mining techniques to automate failure diagnosis on the back-end. The assumption is that the occurrence of execution conditions that cause failures (e.g., traversal of an execution path that contains a "bug" or occurrence of a sequence of events that a protocol was not designed to handle) will have a measurable correlation (by causality) with the resulting failure itself. Hence, by mining for network conditions that correlate with failure states the root causes of failure are revealed with high probability. To evaluate the effectiveness of the tool, we have used it to troubleshoot a tracking system called EnviroTrack [4], which, although performs well most of the time, occasionally fails to track targets correctly. Results show that SNTS can identify the major causes of the problem and give developers useful hints on improving the performance of the tracking system.

关键词： sensor network data mining distributed troubleshooting

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A semantics-based middleware for utilizing heterogeneous sensor networks 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Eric Bouillet Mark Feblowitz Zhen Liu Anand Ranganathan Anton Riabov Fan Ye IBM T.J. Watson Research Center Hawthorne NY

ISBN: (纸本)9783540730897

With the proliferation of various kinds of sensor networks, we will see large amounts of heterogeneous data. They have different characteristics such as data content, formats, modality and quality. Existing research has largely focused on issues related to individual sensor networks; how to make use of diverse data beyond the individual network level is largely unaddressed. In this paper, we propose a semantics-based approach for this problem and describe a system that constructs applications that utilize many sources of data simultaneously. We propose models to formally describe the semantics of data sources, and processing modules that perform various kinds of operations on data. Based on such formal semantics, our system composes data sources and processing modules together in response to users queries. The semantics provides a common ground such that data sources and processing modules from various parties can be shared and reused among applications. We describe our system architecture, illustrate application deployment, and share our experiences in the semantic approach.

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Localization for anchoritic sensor networks 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： Yuliy Baryshnikov Jian Tan Bell Laboratories Murray Hill NJ Department of Electrical Engineering Columbia University New York NY

ISBN: (纸本)9783540730897

We introduce a class of anchoritic sensor networks, where communications between sensor nodes are undesirable or infeasible due to, e.g., harsh environments, energy constraints, or security considerations. Instead, we assume that the sensors buffer the measurements over the lifetime and report them directly to a sink without necessarily requiring communications. Upon retrieval of the reports, all sensor data measurements will be available to a central entity for post *** algorithm is based on the further assumption that some of the data fields that are being observed by the sensors can be modeled as a local (i.e. having decaying spatial correlations) stochastic process; if not, then choose an auxiliary field, e.g., carefully engineered random signals intentionally generated by arranged devices, "cloud shadows" cast on the ground, or animal heat. The sensor nodes record the measurements, or a function of the measurements, e.g., "1" when the measured signal is above a threshold, and "0" otherwise. These time-stamped sequences are ultimately transferred to the sink. The localization problem is then approached by analyzing the correlations between these sequences at pairs of *** for applications, we discuss the localization scheme for large-scaled sensor networks deployed on the seabed and study a two-tiered architecture that organizes deaf sensors with local masters.

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Optimal cluster association in two-tiered wireless sensor networks 07

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Proceedings of the 3rd ieee international conference on distributed computing in sensor systems

作者： WeiZhao Wang Wen-Zhan Song Xiang-Yang Li Kousha Moaveni-Nejad Google Inc. Washington State University Illinois Institute of Technology

ISBN: (纸本)9783540730897

In this paper, we study the two-tiered wireless sensor network (WSN) architecture and propose the optimal cluster association algorithm for it to maximize the overall network lifetime. A two-tiered WSN is formed by number of small sensor nodes (SNs), powerful application nodes (ANs), and base-stations (BSs, or gateways). SNs capture, encode, and transmit relevant information to ANs, which then send the combined information to BSs. Assuming the locations of the SNs, ANs, and BSs are fixed, we consider how to associate the SNs to ANs such that the network lifetime is maximized while every node meets its bandwidth requirement. When the SNs are homogeneous (e.g., same bandwidth requirement), we give optimal algorithms to maximize the lifetime of the WSNs; when the SNs are heterogeneous, we give a 2-approximation algorithm that produces a network whose lifetime is within 1/2 of the optimum. We also present algorithms to dynamically update the cluster association when the network topology changes. Numerical results are given to demonstrate the efficiency and optimality of the proposed approaches. In simulation study, comparing network lifetime, our algorithm outperforms other heuristics almost twice.

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Conceptual Challenges and Practical Issues in Building The Global Lake Ecological Observatory Network

Conceptual Challenges and Practical Issues in Building The G...

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Intelligent sensors, sensor Networks and Information Processing conference (ISSNIP)

作者： Sameer Tilak Peter Arzberger David Balsiger Barbara Benson Rohit Bhalerao Kenneth Chiu Tony Fountain David Hamilton Paul Hanson Tim Kratz Fang-Pang Lin Tim Meinke Luke Winslow University of California San Diego Center for Limnology University of Wisconsin-Madison Computer Science Department USA Centre for Biodiversity and Ecology Research University of Waikato New Zealand Trout Lake Station University of Wisconsin-Madison National Center for High Performance Computing Taiwan University of California San Diego USA

Freshwater lakes provide a number of important ecosystem services such as supply of drinking water, support of biotic diversity, transportation of commercial goods, and opportunity for recreation. Wireless sensor networks allow continuous, fine-grained, in situ measurements of key variables such as water temperature, dissolved gases, pH, conductivity, and chlorophyll. Instrumenting lakes with sensors capable of sampling environmental variables is becoming a standard practice. Furthermore, many limnologists around the world are interested in getting access to and performing research on data collected from lakes around the globe to provide local, regional and even global understanding of lake ecosystems. To that end, a number of limnologists, information technology experts, and engineers have joined forces to create a new, grassroots, international network, the Global Lake Ecological Observatory Network. One of our goals is to build a global scalable, persistent network of lake ecology observatories. However, implementing and designing technology that meets requirements of a large-scale distributed observing systems such as GLEON has, thus far, been challenging and instructive. In this paper, we describe several key conceptual challenges in building GLEON network. We also describe several practical issues and lessons learned during operation of a typical GLEON site.

关键词： Lakes Observatories Ecosystems Transportation Wireless sensor networks Conductivity measurement Temperature sensors Gases Instruments Biosensors

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